The serine protease 2 gene regulates lipid metabolism through the LEP/ampkα1/SREBP1 pathway in bovine mammary epithelial cells

Molecular breeding has brought about significant transformations in the milk market and production system during the twenty-first century. The primary economic characteristic of dairy production pertains to milk fat content. Our previous transcriptome analyses revealed that serine protease 2 (PRSS2) is a candidate gene that could impact milk fat synthesis in bovine mammary epithelial cells (BMECs) of Chinese Holstein dairy cows. To elucidate the function of the PRSS2 gene in milk fat synthesis, we constructed vectors for PRSS2 overexpression and interference and assessed intracellular triglycerides (TGs), cholesterol (CHOL), and nonesterified fatty acid (NEFA) contents in BMECs. Fatty acid varieties and components were also quantified using gas chromatography‒mass spectrometry (GC‒MS) technology. The regulatory pathway mediated by PRSS2 was validated through qPCR, ELISA, and WB techniques. Based on our research findings, PRSS2 emerges as a pivotal gene that regulates the expression of associated genes, thereby making a substantial contribution to lipid metabolism via the leptin (LEP)/Adenylate-activated protein kinase, alpha 1 catalytic subunit (AMPKα1)/sterol regulatory element binding protein 1(SREBP1) pathway by inhibiting TGs and CHOL accumulation while potentially promoting NEFA synthesis in BMECs. Furthermore, the PRSS2 gene enhances intracellular medium- and long-chain fatty acid metabolism by modulating genes related to the LEP/AMPKα1/SREBP1 pathway, leading to increased contents of unsaturated fatty acids C17:1N7 and C22:4N6. This study provides a robust theoretical framework for further investigation into the underlying molecular mechanisms through which PRSS2 influences lipid metabolism in dairy cows.

Genetic correlations between fertility traits and milk composition and fatty acids in Holstein-Friesian, Brown Swiss, and Simmental cattle using recursive models

This study aimed to investigate the genetic and putative causal relationships between fertility traits [i.e., days open (DO) and calving rate (CR)] and milk quality, composition, and fatty acid contents (milk composition traits) in Holstein-Friesian, Brown Swiss, and Simmental cattle, using recursive models within a Bayesian framework. Trivariate animal models were run, each including one fertility trait, one milk composition trait, and, in all models, milk yield. The DO and CR data were merged with the test days closest to the insemination date for milk composition traits. After editing, 16,468 to 23,424 records for Holstein-Friesian, 23,424 to 46,660 for Brown Swiss, and 26,105 to 35,574 for Simmental were available for the analyses. Recursive animal models were applied to investigate the possible causal influences of milk composition traits on fertility and the genetic relationships among these traits. The results suggested a potential cause-and-effect relationship between milk composition traits and fertility traits, with the first trait influencing the latter. We also found greater recursive effects of milk composition traits on DO than on CR, the latter with some putative differences among breeds in terms of sensitivity. For instance, the putative causal effects of somatic cell score on CR (on the observed scale, %) varied from -0.96 to -1.39%, depending on the breed. Concerning fatty acids, we found relevant putative effects of C18:0 on CR, with estimates varying from -7.8 to -9.9%. Protein and casein percentages, and short-chain fatty acid showed larger recursive effects on CR, whereas fat, protein, and casein percentages, C16:0, C18:0, and long-chain fatty acid had larger effects on DO. The results obtained suggested that these milk traits could be considered as effective indicators of the effects of animal metabolic and physiological status on fertility.

Estimation of genetic parameters for mid-infrared-predicted lactoferrin and milk fat globule size in Holstein cattle

Lactoferrin (LF) and milk fat globule (MFG) are 2 biologically active components of milk with great economical and nutritional value in the dairy industry. The objectives of this study were to estimate (1) the heritability of mid-infrared (MIR)-predicted LF and MFG size (MFGS) and (2) the genetic correlations between predicted LF and MFGS with milk, fat, and protein yields, fat and protein percentages, and somatic cell score in first-parity Canadian Holstein cattle. A total of 109,029 test-day records from 22,432 cows and 1,572 farms for MIR-predicted LF and 109,212 test-day records from 22,424 cows and 1,559 farms for MIR-predicted MFGS were used in the analyses. Four separate 5-trait random regression test-day models were used. The models included days in milk, herd test date, and a polynomial regression on DIM nested in age-season of calving classes as fixed effects, random polynomial regressions on DIM nested in herd-year of calving, animal additive genetic and permanent environment classes, and a residual effect. Regression curves were modeled using orthogonal Legendre polynomials of order 4 for the fixed age-season of calving effect and of order 5 for the random effects. Moderate overall heritability estimates of 0.34 and 0.46 were estimated for the MIR-predicted LF and MIR-predicted MFGS, respectively. These heritability estimates were similar to the ones estimated for the direct measure of MFGS in a previous study. The genetic correlations between predicted MFGS and fat percentage (0.53) and between predicted LF and protein percentage (0.41) were both moderate and positive. Predicted LF and somatic cell score showed a weaker correlation (0.06) compared with other studies. The moderate genetic correlation between MIR-predicted MFGS and fat percentage and between MIR-predicted LF and protein percentage suggests that MIR predictions of MFGS and LF are not simply a function of the amount of fat and protein percentage, respectively, in the milk (i.e., the prediction equations are not simply predicting fat or protein percentages). Thus, these MIR-predicted values may provide additional information for selecting for fine milk components in Holstein cattle.

Magnetic separation of phosphate contaminants from starch wastewater using magnetic seeding

Traditional chemical precipitation of phosphates from wastewater is somewhat inefficient because it produces some ultrafine hydroxyapatite particles that are difficult to settle. In this study, magnetic seeds with a core-shell structure were prepared by sulfation roasting for magnetic flocculation of those fine particles. Zeta potential measurements show that the hydroxyapatite particles are positively charged at pH 10, whereas the magnetic seeds are negatively charged. The Derjaguin-Landau-Verwey-Overbeek calculation indicates that the van der Waals force between the magnetic seeds and hydroxyapatite particles is always attractive. Moreover, the electrostatic attraction also contributes to aggregation of the magnetic seeds and hydroxyapatite particles. Orthogonal experiments show that the main factor affecting the magnetic flocculation is the dosage of magnetic seeds, and polymeric ferric sulfate also plays an important role. Under the optimal magnetic flocculation experimental conditions, the turbidity of wastewater after magnetic separation was only 16.388 NTU, contributing to the removal of phosphate contaminants. Therefore, magnetic flocculation and magnetic separation may provide an alternative solution for efficient purification of phosphate-containing wastewater.

A landscape of the heritability of Fourier-transform infrared spectral wavelengths of milk samples by parity and lactation stage in Holstein cows

Fourier-transform near- and mid-infrared (FTIR) milk spectral data are routinely collected in many countries worldwide. Establishing an optimal strategy to use spectral data in genetic evaluations requires knowledge of the heritabilities of individual FTIR wavelength absorbances. Previous FTIR heritability estimates have been based on relatively small sample sizes and have not considered the possibility that heritability may vary across parities and stages of the lactation. We used data from ∼370,000 test-day records of Canadian Holstein cows to produce a landscape of the heritability of FTIR spectra, 1,060 wavelengths in the near- and mid-infrared spectrum (5,011-925 cm^-1), by parity and month of the lactation (mo 1 to 3 and mo 1 to 6, respectively). The 2 regions of the spectrum associated with absorption of electromagnetic energy by water molecules were estimated to have very high phenotypic variances, very low heritabilities, and very low proportion of variance explained by herd-year-season (HYS) subclasses. The near- or short-wavelength infrared (SWIR: 5,066-3,672 cm^-1) region was also characterized by low heritability estimates, whereas the estimated proportion of the variance explained by HYS was high. The mid-wavelength infrared region (MWIR: 3,000-2,500 cm^-1) and the transition between mid and long-wavelength infrared region (MWIR-LWIR: 1,500-925 cm^-1) harbor several waves characterized by moderately high (≥0.4) heritabilities. Most of the high-heritability regions contained wavelengths that are reported to be associated with important milk metabolites and components. Interestingly, these 2 same regions tended to show more variability in heritabilities between parity and lactation stage. Second parity showed heritability patterns that were distinctly different from those of the first and third parities, whereas the first 2 mo of the lactation had clearly distinct heritability patterns compared with mo 3 to 6.